Sensory quality evaluation of rice using visible and shortwave near-infrared spectroscopy

International Journal of Food Properties

Volumn 18, Issue 5, 2015, Pages 1128-1138

  Lapchareonsuk, Ravipat ^a   Sirisomboon, Panmanas ^a  

^a KING MONGKUT'S INSTITUTE OF TECHNOLOGY LADKRABANG   (Thailand)

Author keywords

Near infrared spectroscopy; Rice; Sensory qualities; Shortwave; Visible

Indexed keywords

ADHESIVES; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; NEAR INFRARED SPECTROSCOPY; ODORS;

PARTIAL LEAST SQUARES REGRESSION; RICE; SENSORY ATTRIBUTES; SENSORY PANELS; SENSORY QUALITIES; SHORT-WAVE NEAR-INFRARED; SHORTWAVE; VISIBLE;

QUALITY CONTROL;

JASMINUM;

EID: 84923803317     PISSN: 10942912     EISSN: 15322386     Source Type: Journal    
DOI: 10.1080/10942912.2013.870572     Document Type: Article

References (21)

1. Yoo J., Alavi S., Adhikari K., Haub M.D., Aberle R.A., Huber G. Rice-shaped extruded kernels: Physical sensory and nutritional properties. International Journal of Food Properties 2013, 16 (2), 301-321
2. Yang X.Y., Lin Z.M., Liu Z.H., Alim Md. A., Bi, J.G., Li, G.H.;Wang Q.S.;Wang S.H., Ding Y.F. Physicochemical and sensory properties of japonica rice varied with production areas in China. Journal of Integrative Agriculture 2013, 12 (10), 1748-1756
3. Kam K., Murray J.M., Arcot J., Ward R. fortification of parboiled rice with folic acid: Consumer acceptance and sensory evaluation. Food Research International 2012, 49 (1), 354-363
4. Pestoríc, M., Pojíc, M., Sakəc, M., Mastilovíc, J., Šimurina O., Filipcev B., Živaňcev J. Selection of optimal sensory properties for the recognition of wholemeal bread. International Journal of Food Properties 2012, 15 (4), 748-757
5. Álvarez M.D., Fernández C., Olivares M.D., Jiménez M.J., CanetW. Sensory and texture properties of mashed potato incorporated with inulin and olive oil blends. International Journal of Food Properties 2013, 16 (8), 1839-1859
6. Sicard M., Perrot N., Reuillon R., Mesmoudi S., Alvarez I., Martin S. A viability approach to control food processes: Application to a Camembert cheese ripening process. Food Control 2012, 23 (2), 312-319
7. Ribeiro J.S., Ferreira M.M.C., Salva T.J.G. Chemometric models for the quantitative descriptive sensory analysis of Arabica coffee beverages using near infrared spectroscopy. Talanta 2011, 83 (5), 1352-1358
8. Ferrer-Gallego R., Hernández-Hierro J.M., Rivas-Gonzalo J.C., Escribano-Bailón M.T. Evaluation of sensory parameters of grapes using near infrared spectroscopy. Journal of Food Engineering 2013, 118 (3), 333-339
9. Parpinello G.P., Nunziatini G., Rombolà A.D., Gottardi F., Versari A. Relationship between sensory and NIR spectroscopy in consumer preference of table grape (CV Italia). Postharvest Biology and Technology 2013, 83, 47-53
10. González-Martín M.I., Severiano-Pérez P., Revilla I., Vivar-Quintana A. M., Hernández-Hierro J. M., González-Pérez C., Lobos-Ortega I.A. Prediction of sensory attributes of cheese by near-infrared spectroscopy. Food Chemistry 2011, 127 (1), 256-263
11. Sinelli N., Cerretani L., Egidio V.D., Bendini A., Casiraghi E. Application of near (NIR) infrared and mid (MIR) infrared spectroscopy as a rapid tool to classify extra virgin olive oil on the basis of fruity attribute intensity. Food Research International 2010, 43 (1), 369-375
12. Prieto N., Ross D.W., Navajas E.A., Nute G.R., Richardson R.I., Hyslop J.J., Simm G., Roehe R. On-line application of visible and near infrared reflectance spectroscopy to predict chemical-physical and sensory characteristics of beef quality. Meat Science 2009, 83 (1), 96-103
13. Shimizu N. Evaluating techniques for rice grain quality using near infrared transmission spectroscopy. Journal of Near Infrared Spectroscopy 1998, 6 (A), 111-116
14. Srisawas W., Jindal V.K., Thanapase W., Terdwongworakul A. Relationship between sensory textural attributes and nir spectroscopy of cooked rice. Journal of Near Infrared Spectroscopy 2007, 15 (3), 333-340
15. Meullenet J.F., Mairomoustakos A., Horner T.B., Marks B.P. Prediction of texture of cooked white rice by nearinfrared reflectance analysis of whole-grain milled sample. Cereal Chemistry 2002, 79 (1), 52-57
16. Champagne E.T., Bett-Garber K.L., Grimm C.C., McClung A.M., Moldenhauer K.A., Linscombe S., McKenzie K.S., Barton II, F.E. Near infrared reflectance analysis for prediction of cooked rice texture. Cereal Chemistry 2001, 78 (3), 358-362
17. Windham W.R., Lyon B.G., Champagne E.T., Barton II, F.E., Webb B.D., McClung A.M., Moldenhauer K.A., Linscombe S., McKenzie K.S. Prediction of cooked rice texture quality using near-infrared reflectance analysis of whole-grain milled rice. Cereal Chemistry 1997, 74 (5), 626-632
18. Qingyun L., Yeming C., Mikami T., Kawano M., Zaigui L. Adaptability of four-samples sensory tests and prediction of visual and near-infrared reflectance spectroscopy for Chinese indica rice. Journal of Food Engineering 2007, 79 (4), 1445-1451
19. Lapcharoensuk R., Sirisomboon P. Eating quality of cooked rice determination using fourier transform near infrared spectroscopy. Journal of Innovative Optical Health Sciences 2014, 7 (6), 1450003
20. Osborne B.G., Fearn T. Near Infrared Spectroscopy in Food Analysis 1st Ed., Longman Science & Technical: Essex UK, 1986; Chapter 2
21. Huang S.H., Ng, L.T. Quantification of polyphenolic content and bioactive constituents of some commercial rice varieties in Taiwan. Journal of Food Composition and Analysis 2012, 26 (1-2), 122-127